HBase 组件安装与配置
1.1. 实验目的
完成本实验，您应该能够：
掌握 HBase 安装与配置
掌握 HBase 常用 Shell 命令
1.2. 实验要求
了解 HBase 原理
熟悉 HBase 常用 Shell 命令
1.3. 实验环境
本实验所需之主要资源环境如表 1-1 所示。
表 1-1 资源环境
| 服务器集群 | 单节点，机器最低配置：双核 CPU、8GB 内存、100G 硬盘 |
|---|---|
| 运行环境 | CentOS.7.3 |
| 服务和组件 | 服务和组件根据实验需求安装 |
1.4. 实验过程
1.4.1. 实验任务一：HBase 安装与配置
1.4.1. 实验任务一：HBase 安装与配置
[root@master ~]# tar xf hbase-1.2.1-bin.tar.gz -C /usr/local/src
[root@master ~]# cd /usr/local/src
[root@master src]# ls
hadoop hbase-1.2.1 hive jdk zookeeper
1.4.1.2. 步骤二：重命名 HBase 安装文件夹
[root@master src]# mv hbase-1.2.1/ hbase
[root@master src]# ls
hadoop hbase hive jdk zookeeper
1.4.1.3. 步骤三：在所有节点添加环境变量
[root@master src]# vi /etc/profile.d/hb.sh
在文件中添加
export HBASE_HOME=/usr/local/src/hbase
export PATH=$HBASE_HOME/bin:$PATH
1.4.1.4. 步骤四：在所有节点使环境变量生效
[root@master src]# source /etc/profile.d/hb.sh
1.4.1.5. 步骤五：在 master 节点进入配置文件目录
[root@master src]# cd hbase/conf/
[root@master conf]#
1.4.1.6. 步骤六：在 master 节点配置 hbase-env.sh 文件
[root@master conf]# vi hbase-env.sh
#Java 安装位置 export JAVA_HOME=/usr/local/src/jdk
#值为 true 使用 HBase 自带的 ZooKeeper,值为 false 使用在 Hadoop 上装的 ZooKeeper export HBASE_MANAGES_ZK=false
#HBase 类路径 export HBASE_CLASSPATH=/usr/local/src/hadoop/etc/hadoop/
#注释下面这两句话
# export HBASE_MASTER_OPTS="$HBASE_MASTER_OPTS -XX:PermSize=128m -XX:MaxPermSize=128m"
# export HBASE_REGIONSERVER_OPTS="$HBASE_REGIONSERVER_OPTS -XX:PermSize=128m -XX:MaxPermSize=128m"
1.4.1.7. 步骤七：在 master 节点配置 hbase-site.xml
<configuration>
<property>
<name>hbase.rootdir</name>
<value>hdfs://master:9000/hbase</value>
<description>The directory shared by region servers.</description>
</property>
<property>
<name>hbase.master.info.port</name>
<value>60010</value>
</property>
<property>
<name>hbase.zookeeper.property.clientPort</name>
<value>2181</value>
<description>Property from ZooKeeper's config zoo.cfg. The port at which the clients will connect.</description>
</property>
<property>
<name>zookeeper.session.timeout</name>
<value>12000</value>
</property>
<property>
<name>hbase.zookeeper.quorum</name>
<value>master,slave1,slave2</value>
</property>
<property>
<name>hbase.tmp.dir</name>
<value>/usr/local/src/hbase/tmp</value>
</property>
<property>
<name>hbase.cluster.distributed</name>
<value>true</value>
</property>
</configuration>
hbase.rootdir：该项配置了数据写入的目录，默认 hbase.rootdir是指向/tmp/hbase
${user.name}，也就说你会在重启后丢失数据(重启的时候操作系统会清理/tmp 目录)。
hbase.zookeeper.property.clientPort：指定 zk 的连接端口
zookeeper.session.timeout：RegionServer 与 ZooKeeper 间的连接超时时间。当超
时时间到后，ReigonServer 会被 ZooKeeper 从 RS 集群清单中移除，HMaster 收到移除通
知后，会对这台 server 负责的 regions 重新 balance，让其他存活的 RegionServer 接管.
hbase.zookeeper.quorum：默认值是 localhost，列出 zookeepr ensemble 中的servers
hbase.master.info.port：浏览器的访问端口
1.4.1.8. 步骤八：在 master 节点修改 regionservers 文件
#删除 localhost，每一行写一个 slave 节点主机机器名
[root@master conf]# vi regionservers
[root@master conf]# cat regionservers
slave1
slave2
1.4.1.9. 步骤九：在 master 节点创建 hbase.tmp.dir 目录
[root@master conf]# mkdir /usr/local/src/hbase/tmp
1.4.1.10. 步骤十：将 master 上的 hbase 安装文件同步到 slave1 slave2
[root@master conf]# scp -r /usr/local/src/hbase/ root@slave1:/usr/local/src/
root@slave1's password:
[root@master conf]# scp -r /usr/local/src/hbase/ root@slave2:/usr/local/src/
root@slave2's password:
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1.4.1.11. 步骤十一：在所有节点修改 hbase 目录权限
[root@master conf]# chown -R hadoop:hadoop /usr/local/src/hbase/
[root@slave1 ~]# chown -R hadoop:hadoop /usr/local/src/hbase/
[root@slave2 ~]# chown -R hadoop:hadoop /usr/local/src/hbase/
1.4.1.12. 步骤十二：在所有节点切换到 hadoop 用户
[root@master conf]# su - hadoop
Last login: Tue Mar 28 22:26:59 EDT 2023 on pts/0
[root@slave1 ~]# su - hadoop
Last login: Tue Mar 28 22:29:25 EDT 2023 on pts/0
[root@slave2 ~]# su - hadoop
Last login: Tue Mar 28 22:32:42 EDT 2023 on pts/0
1.4.1.13. 步骤十三：启动 HBase
先启动 Hadoop，然后启动 ZooKeeper，最后启动 HBase。
首先在 master 节点启动 Hadoop。
[hadoop@master ~]$ start-all.sh
This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh
Starting namenodes on [master]
master: starting namenode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-namenode-master.out
slave1: starting datanode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-datanode-slave1.out
slave2: starting datanode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-datanode-slave2.out
192.168.10.20: ssh: connect to host 192.168.10.20 port 22: Connection refused
192.168.10.30: ssh: connect to host 192.168.10.30 port 22: Connection refused
Starting secondary namenodes [0.0.0.0]
0.0.0.0: starting secondarynamenode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-secondarynamenode-master.out
starting yarn daemons
starting resourcemanager, logging to /usr/local/src/hadoop/logs/yarn-hadoop-resourcemanager-master.out
slave1: starting nodemanager, logging to /usr/local/src/hadoop/logs/yarn-hadoop-nodemanager-slave1.out
slave2: starting nodemanager, logging to /usr/local/src/hadoop/logs/yarn-hadoop-nodemanager-slave2.out
192.168.10.20: ssh: connect to host 192.168.10.20 port 22: Connection refused
192.168.10.30: ssh: connect to host 192.168.10.30 port 22: Connection refused
#master 节点
[hadoop@master ~]$ jps
1696 SecondaryNameNode
1493 NameNode
2119 Jps
1855 ResourceManager
#slave1 节点
[hadoop@slave1 ~]$ jps
1504 NodeManager
1629 Jps
1390 DataNode
#slave2 节点
[hadoop@slave2 ~]$ jps
1325 DataNode
1565 Jps
1439 NodeManager
1.4.1.14. 步骤十四：在所有节点启动 ZooKeeper
master 节点
[hadoop@master ~]$ zkServer.sh start
ZooKeeper JMX enabled by default
Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg
Starting zookeeper ... STARTED
[hadoop@master ~]$ jps
1696 SecondaryNameNode
2145 QuorumPeerMain
1493 NameNode
2165 Jps
1855 ResourceManager
slave1 节点
[hadoop@slave1 ~]$ zkServer.sh start
ZooKeeper JMX enabled by default
Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg
Starting zookeeper ... STARTED
[hadoop@slave1 ~]$ jps
1504 NodeManager
1680 Jps
1651 QuorumPeerMain
1390 DataNode
slave2 节点
[hadoop@slave2 ~]$ zkServer.sh start
ZooKeeper JMX enabled by default
Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg
Starting zookeeper ... STARTED
[hadoop@slave2 ~]$ jps
1587 QuorumPeerMain
1610 Jps
1325 DataNode
1439 NodeManager
1.4.1.15. 步骤十五：在 master 节点启动 HBase
[hadoop@master ~]$ start-hbase.sh
master: starting zookeeper, logging to /usr/local/src/hbase/logs/hbase-hadoop-zookeeper-master.out
slave1: starting zookeeper, logging to /usr/local/src/hbase/bin/../logs/hbase-hadoop-zookeeper-slave1.out
slave2: starting zookeeper, logging to /usr/local/src/hbase/bin/../logs/hbase-hadoop-zookeeper-slave2.out
starting master, logging to /usr/local/src/hbase/logs/hbase-hadoop-master-master.out
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option PermSize=128m; support was removed in 8.0
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0
slave1: starting regionserver, logging to /usr/local/src/hbase/bin/../logs/hbase-hadoop-regionserver-slave1.out
slave2: starting regionserver, logging to /usr/local/src/hbase/bin/../logs/hbase-hadoop-regionserver-slave2.out
slave1: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option PermSize=128m; support was removed in 8.0
slave1: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0
slave2: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option PermSize=128m; support was removed in 8.0
slave2: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0
master 节点
[hadoop@master ~]$ jps
1696 SecondaryNameNode
2496 HMaster
2145 QuorumPeerMain
1493 NameNode
2713 Jps
1855 ResourceManager
2399 HQuorumPeer
slave1 节点
[hadoop@slave1 ~]$ jps
1504 NodeManager
53826 Jps
1651 QuorumPeerMain
30633 HRegionServer
1390 DataNode
slave2节点
[hadoop@slave2 ~]$ jps
1587 QuorumPeerMain
1769 HRegionServer
1325 DataNode
1439 NodeManager
1983 Jps
1.4.1.16. 步骤十六：在浏览器输入 master:60010 出现如下图 7-2 所示的界面。
1.4.2. 实验任务二：HBase 常用 Shell 命令
启动 hdfs、zookeeper、hbase 服务
1.4.2.1. 步骤一：进入 HBase 命令行
[hadoop@master ~]$ hbase shell
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/src/hbase/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/src/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
HBase Shell; enter 'help<RETURN>' for list of supported commands.
Type "exit<RETURN>" to leave the HBase Shell
Version 1.2.1, r8d8a7107dc4ccbf36a92f64675dc60392f85c015, Wed Mar 30 11:19:21 CDT 2016
hbase(main):001:0>
1.4.2.2. 步骤二：建立表 scores，两个列簇：grade 和 course
hbase(main):001:0> create 'scores','grade','course'
0 row(s) in 1.3750 seconds
=> Hbase::Table - scores
1.4.2.3. 步骤三：查看数据库状态
hbase(main):002:0> status
1 active master, 0 backup masters, 2 servers, 0 dead, 1.5000 average load
1.4.2.4. 步骤四：查看数据库版本
hbase(main):003:0> version
1.2.1, r8d8a7107dc4ccbf36a92f64675dc60392f85c015, Wed Mar 30 11:19:21 CDT 2016
1.4.2.5. 步骤五：查看表
hbase(main):004:0> list
TABLE
scores
1 row(s) in 0.0180 seconds
=> ["scores"]
1.4.2.6. 步骤六：插入记录 1：jie,grade: 143cloud
hbase(main):005:0> put 'scores','jie','grade:','146cloud'
0 row(s) in 0.0960 seconds
1.4.2.7. 步骤七：插入记录 2：jie,course:math,86
hbase(main):006:0> put 'scores','jie','course:math','86'
0 row(s) in 0.0080 seconds
1.4.2.8. 步骤八：插入记录 3：jie,course:cloud,92
hbase(main):007:0> put 'scores','jie','course:cloud','92'
0 row(s) in 0.0080 seconds
1.4.2.9. 步骤九：插入记录 4：shi,grade:133soft
hbase(main):010:0> put 'scores','shi','grade:','133soft'
0 row(s) in 0.0070 seconds
1.4.2.10. 步骤十：插入记录 5：shi,grade:math,87
hbase(main):011:0> put 'scores','shi','course:math','87'
0 row(s) in 0.0080 seconds
1.4.2.11. 步骤十一：插入记录 6：shi,grade:cloud,96
hbase(main):012:0> put 'scores','shi','course:cloud','96'
0 row(s) in 0.0070 seconds
1.4.2.12. 步骤十二：读取 jie 的记录
hbase(main):013:0> get 'scores','jie'
COLUMN CELL
course:cloud timestamp=1680168819550, value=92
course:math timestamp=1680168788779, value=86
grade: timestamp=1680168764754, value=146cloud
3 row(s) in 0.0190 seconds
1.4.2.13. 步骤十三：读取 jie 的班级
hbase(main):014:0> get 'scores','jie','grade'
COLUMN CELL
grade: timestamp=1680168764754, value=146cloud
1 row(s) in 0.0070 seconds
1.4.2.14. 步骤十四：查看整个表记录
hbase(main):015:0> scan 'scores'
ROW COLUMN+CELL
jie column=course:cloud, timestamp=1680168819550, value=92
jie column=course:math, timestamp=1680168788779, value=86
jie column=grade:, timestamp=1680168764754, value=146cloud
shi column=course:cloud, timestamp=1680168898986, value=96
shi column=course:math, timestamp=1680168879674, value=87
shi column=grade:, timestamp=1680168856040, value=133soft
2 row(s) in 0.0180 seconds
1.4.2.15. 步骤十五：按例查看表记录
hbase(main):016:0> scan 'scores',{COLUMNS=>'course'}
ROW COLUMN+CELL
jie column=course:cloud, timestamp=1680168819550, value=92
jie column=course:math, timestamp=1680168788779, value=86
shi column=course:cloud, timestamp=1680168898986, value=96
shi column=course:math, timestamp=1680168879674, value=87
2 row(s) in 0.0110 seconds
1.4.2.16. 步骤十六：删除指定记录
hbase(main):017:0> delete 'scores','shi','grade'
0 row(s) in 0.0200 seconds
1.4.2.17. 步骤十七：删除后，执行 scan 命令
hbase(main):001:0> scan 'scores'
ROW COLUMN+CELL
jie column=course:cloud, timestamp=1680168819550, value=92
jie column=course:math, timestamp=1680168788779, value=86
jie column=grade:, timestamp=1680168764754, value=146cloud
shi column=course:cloud, timestamp=1680168898986, value=96
shi column=course:math, timestamp=1680168879674, value=87
2 row(s) in 0.2670 seconds
1.4.2.18. 步骤十八：增加新的列簇
2 row(s) in 0.2670 seconds
hbase(main):002:0> alter 'scores',NAME=>'age'
Updating all regions with the new schema...
1/1 regions updated.
Done.
0 row(s) in 2.0020 seconds
1.4.2.19. 步骤十九：查看表结构
hbase(main):004:0> describe 'scores'
Table scores is ENABLED
scores
COLUMN FAMILIES DESCRIPTION
{NAME => 'age', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CELL
S => 'FALSE', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VERS
IONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'}
{NAME => 'course', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_C
ELLS => 'FALSE', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_V
ERSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'}
{NAME => 'grade', BLOOMFILTER => 'ROW', VERSIONS => '1', IN_MEMORY => 'false', KEEP_DELETED_CE
LLS => 'FALSE', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', COMPRESSION => 'NONE', MIN_VE
RSIONS => '0', BLOCKCACHE => 'true', BLOCKSIZE => '65536', REPLICATION_SCOPE => '0'}
3 row(s) in 0.0300 seconds
1.4.2.20. 步骤二十：删除列簇
hbase(main):005:0> alter 'scores',NAME=>'age',METHOD=>'delete'
Updating all regions with the new schema...
1/1 regions updated.
Done.
0 row(s) in 1.9120 seconds
1.4.2.21. 步骤二十一：删除表
hbase(main):006:0> disable 'scores'
0 row(s) in 2.2810 seconds
1.4.2.22. 步骤二十二：退出
hbase(main):008:0> quit
[hadoop@master ~]$
1.4.2.23 步骤二十三：关闭 HBase
在 master 节点关闭 HBase。
[hadoop@master etc]$ stop-hbase.sh
stopping hbase...................
slave2: no zookeeper to stop because no pid file /tmp/hbase-hadoop-zookeeper.pid
master: no zookeeper to stop because no pid file /tmp/hbase-hadoop-zookeeper.pid
slave1: no zookeeper to stop because no pid file /tmp/hbase-hadoop-zookeeper.pid
在所有节点关闭 ZooKeeper。
[hadoop@master etc]$ zkServer.sh stop
ZooKeeper JMX enabled by default
Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg
Stopping zookeeper ... STOPPED
[hadoop@slave1 ~]$ zkServer.sh stop
ZooKeeper JMX enabled by default
Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg
Stopping zookeeper ... STOPPED
[hadoop@slave2 ~]$ zkServer.sh stop
ZooKeeper JMX enabled by default
Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg
Stopping zookeeper ... STOPPED
在 master 节点关闭 Hadoop。
[hadoop@master etc]$ stop-all.sh
This script is Deprecated. Instead use stop-dfs.sh and stop-yarn.sh
Stopping namenodes on [master]
master: stopping namenode
slave2: stopping datanode
slave1: stopping datanode
192.168.10.20: ssh: connect to host 192.168.10.20 port 22: Connection refused
192.168.10.30: ssh: connect to host 192.168.10.30 port 22: Connection refused
Stopping secondary namenodes [0.0.0.0]
0.0.0.0: stopping secondarynamenode
stopping yarn daemons
stopping resourcemanager
slave1: stopping nodemanager
slave2: stopping nodemanager
192.168.10.30: ssh: connect to host 192.168.10.30 port 22: Connection refused
192.168.10.20: ssh: connect to host 192.168.10.20 port 22: Connection refused
no proxyserver to stop
注意：各节点之间时间必须同步，否则 HBase 启动不了。 在每个节点执行 date 命令，查看每个节点的时间是否同步，不同步的话，在各节点执 行 date 命令，date -s "2016-04-15 12:00:00".
2.用hbase自带的zookeeper来调度配置
2.1. 实验任务一：HBase 安装与配置
[root@master ~]# tar xf hbase-1.2.1-bin.tar.gz -C /usr/local/src
[root@master ~]# cd /usr/local/src
[root@master src]# ls
hadoop hbase-1.2.1 hive jdk zookeeper
2.2. 步骤二：重命名 HBase 安装文件夹
[root@master src]# mv hbase-1.2.1/ hbase
[root@master src]# ls
hadoop hbase hive jdk zookeeper
2.3. 步骤三：在所有节点添加环境变量
[root@master src]# vi /etc/profile.d/hb.sh
在文件中添加
export HBASE_HOME=/usr/local/src/hbase
export PATH=$HBASE_HOME/bin:$PATH
2.4. 步骤四：在所有节点使环境变量生效
[root@master src]# source /etc/profile.d/hb.sh
2.5. 步骤五：在 master 节点进入配置文件目录
[root@master src]# cd hbase/conf/
[root@master conf]#
2.6. 步骤六：在 master 节点配置 hbase-env.sh 文件
[root@master conf]# vi hbase-env.sh
Java 安装位置 export JAVA_HOME=/usr/local/src/jdk
#值为 true 使用 HBase 自带的 ZooKeeper,值为 false 使用在 Hadoop 上装的 ZooKeeper export HBASE_MANAGES_ZK=true
#HBase 类路径 export HBASE_CLASSPATH=/usr/local/src/hadoop/etc/hadoop/
#注释下面这两句话
# export HBASE_MASTER_OPTS="$HBASE_MASTER_OPTS -XX:PermSize=128m -XX:MaxPermSize=128m"
# export HBASE_REGIONSERVER_OPTS="$HBASE_REGIONSERVER_OPTS -XX:PermSize=128m -XX:MaxPermSize=128m"
2.7. 步骤七：在 master 节点配置 hbase-site.xml
<configuration>
<property>
<name>hbase.rootdir</name>
<value>hdfs://master:9000/hbase</value>
<description>The directory shared by region servers.</description>
</property>
<property>
<name>hbase.master.info.port</name>
<value>60010</value>
</property>
<property>
<name>hbase.zookeeper.property.clientPort</name>
<value>2181</value>
<description>Property from ZooKeeper's config zoo.cfg. The port at which the clients will connect.</description>
</property>
<property>
<name>zookeeper.session.timeout</name>
<value>12000</value>
</property>
<property>
<name>hbase.zookeeper.quorum</name>
<value>master,slave1,slave2</value>
</property>
<property>
<name>hbase.tmp.dir</name>
<value>/usr/local/src/hbase/tmp</value>
</property>
<property>
<name>hbase.cluster.distributed</name>
<value>true</value>
</property>
</configuration>
hbase.rootdir：该项配置了数据写入的目录，默认 hbase.rootdir是指向/tmp/hbase
${user.name}，也就说你会在重启后丢失数据(重启的时候操作系统会清理/tmp 目录)。
hbase.zookeeper.property.clientPort：指定 zk 的连接端口
zookeeper.session.timeout：RegionServer 与 ZooKeeper 间的连接超时时间。当超
时时间到后，ReigonServer 会被 ZooKeeper 从 RS 集群清单中移除，HMaster 收到移除通
知后，会对这台 server 负责的 regions 重新 balance，让其他存活的 RegionServer 接管.
hbase.zookeeper.quorum：默认值是 localhost，列出 zookeepr ensemble 中的servers
hbase.master.info.port：浏览器的访问端口
2.8. 步骤八：在 master 节点修改 regionservers 文件
#删除 localhost，每一行写一个 slave 节点主机机器名
[root@master conf]# vi regionservers
[root@master conf]# cat regionservers
slave1
slave2
2.9. 步骤九：在 master 节点创建 hbase.tmp.dir 目录
[root@master conf]# mkdir /usr/local/src/hbase/tmp
2.10. 步骤十：将 master 上的 hbase 安装文件同步到 slave1 slave2
[root@master conf]# scp -r /usr/local/src/hbase/ root@slave1:/usr/local/src/
root@slave1's password:
[root@master conf]# scp -r /usr/local/src/hbase/ root@slave2:/usr/local/src/
root@slave2's password:
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2.11. 步骤十一：在所有节点修改 hbase 目录权限
[root@master conf]# chown -R hadoop:hadoop /usr/local/src/hbase/
[root@slave1 ~]# chown -R hadoop:hadoop /usr/local/src/hbase/
[root@slave2 ~]# chown -R hadoop:hadoop /usr/local/src/hbase/
2.12. 步骤十二：在所有节点切换到 hadoop 用户
[root@master conf]# su - hadoop
Last login: Tue Mar 28 22:26:59 EDT 2023 on pts/0
[root@slave1 ~]# su - hadoop
Last login: Tue Mar 28 22:29:25 EDT 2023 on pts/0
[root@slave2 ~]# su - hadoop
Last login: Tue Mar 28 22:32:42 EDT 2023 on pts/0
2.13. 步骤十三：启动 HBase
先启动 Hadoop，然后启动 ZooKeeper，最后启动 HBase。
首先在 master 节点启动 Hadoop。
[hadoop@master ~]$ start-all.sh
This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh
Starting namenodes on [master]
master: starting namenode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-namenode-master.out
slave1: starting datanode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-datanode-slave1.out
slave2: starting datanode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-datanode-slave2.out
192.168.10.20: ssh: connect to host 192.168.10.20 port 22: Connection refused
192.168.10.30: ssh: connect to host 192.168.10.30 port 22: Connection refused
Starting secondary namenodes [0.0.0.0]
0.0.0.0: starting secondarynamenode, logging to /usr/local/src/hadoop/logs/hadoop-hadoop-secondarynamenode-master.out
starting yarn daemons
starting resourcemanager, logging to /usr/local/src/hadoop/logs/yarn-hadoop-resourcemanager-master.out
slave1: starting nodemanager, logging to /usr/local/src/hadoop/logs/yarn-hadoop-nodemanager-slave1.out
slave2: starting nodemanager, logging to /usr/local/src/hadoop/logs/yarn-hadoop-nodemanager-slave2.out
192.168.10.20: ssh: connect to host 192.168.10.20 port 22: Connection refused
192.168.10.30: ssh: connect to host 192.168.10.30 port 22: Connection refused
#master 节点
[hadoop@master ~]$ jps
1696 SecondaryNameNode
1493 NameNode
2119 Jps
1855 ResourceManager
#slave1 节点
[hadoop@slave1 ~]$ jps
1504 NodeManager
1629 Jps
1390 DataNode
#slave2 节点
[hadoop@slave2 ~]$ jps
1325 DataNode
1565 Jps
1439 NodeManager
2.14. 步骤十四：在所有节点启动 ZooKeeper
master 节点
[hadoop@master ~]$ zkServer.sh start
ZooKeeper JMX enabled by default
Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg
Starting zookeeper ... STARTED
[hadoop@master ~]$ jps
1696 SecondaryNameNode
2145 QuorumPeerMain
1493 NameNode
2165 Jps
1855 ResourceManager
slave1 节点
[hadoop@slave1 ~]$ zkServer.sh start
ZooKeeper JMX enabled by default
Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg
Starting zookeeper ... STARTED
[hadoop@slave1 ~]$ jps
1504 NodeManager
1680 Jps
1651 QuorumPeerMain
1390 DataNode
slave2 节点
[hadoop@slave2 ~]$ zkServer.sh start
ZooKeeper JMX enabled by default
Using config: /usr/local/src/zookeeper/bin/../conf/zoo.cfg
Starting zookeeper ... STARTED
[hadoop@slave2 ~]$ jps
1587 QuorumPeerMain
1610 Jps
1325 DataNode
1439 NodeManager
2.15. 步骤十五：在 master 节点启动 HBase
[hadoop@master ~]$ start-hbase.sh
master: starting zookeeper, logging to /usr/local/src/hbase/logs/hbase-hadoop-zookeeper-master.out
slave1: starting zookeeper, logging to /usr/local/src/hbase/bin/../logs/hbase-hadoop-zookeeper-slave1.out
slave2: starting zookeeper, logging to /usr/local/src/hbase/bin/../logs/hbase-hadoop-zookeeper-slave2.out
starting master, logging to /usr/local/src/hbase/logs/hbase-hadoop-master-master.out
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option PermSize=128m; support was removed in 8.0
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0
slave1: starting regionserver, logging to /usr/local/src/hbase/bin/../logs/hbase-hadoop-regionserver-slave1.out
slave2: starting regionserver, logging to /usr/local/src/hbase/bin/../logs/hbase-hadoop-regionserver-slave2.out
slave1: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option PermSize=128m; support was removed in 8.0
slave1: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0
slave2: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option PermSize=128m; support was removed in 8.0
slave2: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=128m; support was removed in 8.0
master 节点
[hadoop@master ~]$ jps
1696 SecondaryNameNode
2496 HMaster
2145 QuorumPeerMain
1493 NameNode
2713 Jps
1855 ResourceManager
2399 HQuorumPeer
slave1 节点
[hadoop@slave1 ~]$ jps
1504 NodeManager
53826 Jps
1651 QuorumPeerMain
30633 HRegionServer
1390 DataNode
slave2节点
[hadoop@slave2 ~]$ jps
1587 QuorumPeerMain
1769 HRegionServer
1325 DataNode
1439 NodeManager
1983 Jps